Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays

Wang Tianyu; Zhu Quanxin; Cai Jingwei

首页> 外文期刊>Mathematical Problems in Engineering >Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays

【24h】

Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays

机译：具有多比例时滞和分布时滞的随机模糊递归神经网络的均方指数输入到状态稳定性

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

We are interested in a class of stochastic fuzzy recurrent neural networks with multiproportional delays and distributed delays. By constructing suitable Lyapunov-Krasovskii functionals and applying stochastic analysis theory, Ito's formula and Dynkin's formula, we derive novel sufficient conditions for mean-square exponential input-to-state stability of the suggested system. Some remarks and discussions are given to show that our results extend and improve some previous results in the literature. Finally, two examples and their simulations are provided to illustrate the effectiveness of the theoretical results.

机译：我们对一类具有多比例时滞和分布时滞的随机模糊递归神经网络感兴趣。通过构建合适的Lyapunov-Krasovskii泛函并应用随机分析理论，伊藤公式和Dynkin公式，我们得出了所建议系统均方指数输入至状态稳定性的新颖充分条件。进行了一些评论和讨论，以表明我们的结果扩展并改进了文献中的某些先前结果。最后，提供了两个例子及其仿真来说明理论结果的有效性。

著录项

来源
《Mathematical Problems in Engineering》 |2018年第13期|6289019.1-6289019.11|共11页
作者
Wang Tianyu; Zhu Quanxin; Cai Jingwei;
展开▼
作者单位

Hunan Normal Univ Coll Math & Stat Key Lab HPC SIP MOE Changsha 410081 Hunan Peoples R China|Nanjing Normal Univ Sch Math Sci Nanjing 210023 Jiangsu Peoples R China|Nanjing Normal Univ Inst Finance & Stat Nanjing 210023 Jiangsu Peoples R China;

Hunan Normal Univ Coll Math & Stat Key Lab HPC SIP MOE Changsha 410081 Hunan Peoples R China;

Jiangsu Polytech Coll Agr & Forestry Basis Dept Zhenjiang 212400 Jiangsu Peoples R China;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词

相似文献

外文文献
中文文献
专利

1. Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays [J] . Tianyu Wang, Quanxin Zhu, Jingwei Cai Mathematical Problems in Engineering: Theory, Methods and Applications . 2018,第3期

机译：具有多比例时滞和分布时滞的随机模糊递归神经网络的均方指数输入到状态稳定性
2. Mean-square exponential input-to-state stability of stochastic recurrent neural networks with multi-proportional delays [J] . Zhou Liqun, Liu Xueting Neurocomputing . 2017,第JANa5期

机译：具有多比例延迟的随机递归神经网络的均方指数输入到状态稳定性
3. Mean-square exponential input-to-state stability for neutral stochastic neural networks with mixed delays [J] . Song Yinfang, Sun Wen, Jiang Feng Neurocomputing . 2016,第sepa12期

机译：具有混合时滞的中立随机神经网络的均方指数输入到状态稳定性
4. Exponential Input-to-State Stability of Stochastic Fuzzy Delayed Cohen-Grossberg Neural Networks Under Impulsive Perturbations [C] . Weisong Zhou, Hao Zeng, Donghai Wu Chinese Control Conference . 2018

机译：脉冲扰动下随机模糊时滞Cohen-Grossberg神经网络的指数输入状态稳定性
5. Exponential Stability of Intrinsically Stable Dynamical Networks and Switched Networks with Time-Varying Time Delays [D] . Reber, David Patrick. 2019

机译：具有时变时间延迟的内在稳定动态网络和交换网络的指数稳定性
6. Exponential input-to-state stability of recurrent neural networks with multiple time-varying delays [O] . Zhichun Yang, Weisong Zhou, Tingwen Huang 2014

机译：具有多个时变时滞的递归神经网络的指数输入到状态稳定性
7. Mean-square exponential input-to-state stability of stochastic recurrent neural networks with multi-proportional delays [O] . Liqun Zhou, Xueting Liu 2017

机译：具有多比例延迟的随机经常性神经网络的平均方形指数输入 - 状态稳定性

Mean-Square Exponential Input-to-State Stability of Stochastic Fuzzy Recurrent Neural Networks with Multiproportional Delays and Distributed Delays

摘要

著录项

相似文献

相关主题

期刊订阅